Search

Establishing a correlation between environmental variables and chemical change can significantly improve the quality of research in multiple fields. Among various environmental variables, temperature and humidity are closely related to the rate of chemical reactions. This study aimed to confirm changes in metabolite markers that were previously discovered in other temperature and humidity environment conditions and to confirm the possibility that they could act as markers. After blood collection from the subjects and bloodstain preparation, the quantitative values of the bloodstain metabolites were confirmed (when the age of the bloodstain was within a month) under eight environmental conditions (4 °C/30%, 4 °C/60%, 25 °C/30%, 25 °C/60%, 25 °C/90%, 40 °C/30%, 40 °C/60%, and 40 °C/90%). Age-of-bloodstain estimation models were constructed to confirm the applicability of bloodstain metabolites as markers for bloodstain age in various environments. The average concentration of metabolite markers exhibited a decreasing trend with the age of the bloodstain, which transformed into an increasing trend from day 7 onwards. In terms of temperature and humidity, 25 °C and 90%, respectively, showed the most dissimilar metabolite change pattern compared to other conditions. The age-of-bloodstain estimation models developed here have an R-square value of up to 0.92 for each condition and an R-square value of 0.71 when all environmental conditions were combined. The findings herein highlight the immense potential of blood metabolites for field application, confirming the possibility of predicting metabolite changes from the rates of their chemical reactions and validating the importance of metabolites as age-of-bloodstain markers under various environmental conditions. • Uncontrolled chemical changes in an ex-vivo environment are poorly understood. • Bloodstains in environmental conditions were examined using metabolomic approach. • Bloodstain metabolites showed the greatest change at 25 °C and 60% relative humidity. • Metabolite marker concentrations showed an increasing trend after 7 days. • Prediction models allowed for estimating the age of bloodstain using metabolites. [ABSTRACT FROM AUTHOR]

Pancreatic adenocarcinoma upregulated factor (PAUF) was initially identified as a secreted protein that is substantially expressed in pancreatic ductal adenocarcinoma (PDAC). PAUF also affects invasiveness, motility, and the proliferation of cells in several types of cancer. Recently, PAUF was reported to play a pivotal role in the TLR4-mediated migration and invasion of PDAC cells. However, the mechanism inducing PAUF expression and its functional role in TGF-β-stimulated PDAC cells have not yet been studied. Thus, we first assessed whether TGF-β regulates PAUF expression in several PDAC cell lines and found a significant increase in PAUF expression in Smad signaling-positive Panc-1 cells treated with TGF-β. We also found that the PAUF promoter region contains a Smad-binding element. TGF-β-treated Panc-1 cells showed an increase in PAUF promoter activity, but this effect was not observed in TGF-β-stimulated Smad4-null BxPC-3 cells. Restoring Smad4 expression increased the PAUF promoter activity and expression in Smad4-overexpressing BxPC-3 cells treated with TGF-β. We further found that PAUF aggravated the TGF-β-induced epithelial-mesenchymal transition (EMT) in Panc-1 and BxPC-3 cells via the activation of MEK-ERK signaling. These results indicate that TGF-β/Smad signaling-mediated upregulation of PAUF plays a crucial role in EMT progression by activating the TGF-β-mediated MEK-ERK signaling pathway.

In patients with major depressive disorder, various functional areas are impaired, negatively impacting the quality of life. Remission can restore pre-depression functions; however, some patients may still have residual impairments. Distinguishing between near-normal recovery and residual impairment helps identify those at a high risk of relapse risk and helps tailor treatment. Accordingly, we aimed to discover and validate biomarkers that distinguish between near-normal recovery and residual impairment in remission states through serum proteome analysis. Pooled serum and individual serum samples from three groups (depression status, remission status with residual impairment, and remission status with normal recovery) were analyzed using liquid chromatography-tandem mass spectrometry. The combination of four proteins-antithrombin-III, serum amyloid A4 protein, C1q subcomponent subunit B, and serum amyloid P-component-was selected as a candidate biomarker. The trend of protein changes suggests complement C1q subcomponent subunit B and serum amyloid P-component as potential biomarkers for distinguishing remission from residual impairment. Changes in complement C1q subcomponent subunit B and serum amyloid P-component suggest that the complement system and inflammation-related immune mechanisms are associated with residual impairment in remittent major depressive disorder., (© 2024. The Author(s).)

Background: Major depressive disorder (MDD) exhibits a recurrence rate of up to 70%. Frequent recurrence can lead to chronic depression, which has considerable personal and societal consequences. This study aims to identify a serum protein biomarker to predict MDD recurrence and progression to chronicity., Methods: Serum samples from the MDD with single episode group (MDD-S), MDD with recurrence group (MDD-R), and a healthy control group were collected. Non-targeted analysis of the serum proteome was conducted using liquid chromatography-tandem mass spectrometry. Statistically significant common proteins when comparing the three groups were chosen. The selected marker candidates were subsequently validated through multiple response monitoring (MRM), incorporating a healthy control, MDD-S, MDD-R(2) (two episodes), and MDD-R(> 2) (more than two episodes) groups., Results: L-selectin levels showed an upward trend in the MDD-R group compared to the healthy control and MDD-S groups. MRM validation revealed a decreased tendency for L-selectin in the MDD-R(> 2) group, indicative of a chronic state, versus the healthy control and MDD-S groups. The receiver operating characteristic analysis highlighted L-selectin as the chosen biomarker due to its classification efficacy for the MDD-R(> 2) group., Conclusion: L-selectin emerged as a predictive biomarker for MDD recurrence and its potential evolution into chronic depression. This marker offers insights into changes in leukocyte-mediated inflammatory responses characteristic of chronic depression. Consequently, it may forecast the transition from acute to chronic inflammation in depressive patients., (© 2024. The Author(s).)

Individual-level georeferenced data have been widely used in COVID-19 control measures around the world. Recent research observed that there is a trade-off relationship between people's privacy concerns and their acceptance of these control measures. However, whether this trade-off relationship exists across different cultural contexts is still unaddressed. Using data we collected via an international survey (n = 4260) and network analysis, our study found a substantial trade-off inter-relationship among people's privacy concerns, perceived social benefits, and acceptance across different control measures and study areas. People's privacy concerns in culturally tight societies (e.g., Japan) have the smallest negative impacts on their acceptance of pandemic control measures. The results also identify people's key views of specific control measures that can influence their views of other control measures. The impacts of these key views are heightened among participants with a conservative political view, high levels of perceived social tightness, and vertical individualism. Our results indicate that cultural factors are a key mechanism that mediate people's privacy concerns and their acceptance of pandemic control measures. These close inter-relationships lead to a double-edged sword effect: the increased positive impacts of people's acceptance and perceived social benefits also lead to increased negative impacts of privacy concerns in different combinations of control strategies. The findings highlight the importance of cultural factors as key determinants that affect people's acceptance or rejection of specific pandemic control measures., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Major depressive disorder (MDD) can present a variety of clinical presentations and has high inter-individual heterogeneity. Multiple studies have suggested various subtype models related to symptoms, etiology, sex, and treatment response. Employing different regimens is common when treating MDD, and identifying effective therapeutics requires time. Frequent treatment attempts and failures can lead to a diagnosis of treatment resistance, and the heterogeneity of treatment responses among individuals makes it difficult to understand and interpret the biological mechanisms underlying MDD., Aim: This study explored the differentially expressed proteins and commonly altered protein networks across drug treatments by comparing the serum proteomes of patients with MDD treated with drug regimens (T-MDD, n  = 20) and untreated patients (NT-MDD, n  = 20)., Methods: Differentially expressed proteins were profiled in non-drug-treated and drug-treated patients with depression using liquid chromatography-mass spectrometry. The common protein networks affected by different medications were studied., Results: Of the proteins profiled, 12 were significantly differentially expressed between the T-MDD and NT-MDD groups. Commonly altered proteins and networks of various drug treatments for depression were related to the complement system and immunity., Conclusions: Our results provide information on common biological changes across different pharmacological treatments employed for depression and provide an alternative perspective for improving our understanding of the biological mechanisms of drug response in MDD with great heterogeneity in the background of the disease., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Residents in areas with abandoned mines risk significant exposure to abundant heavy metals in the environment. However, current clinical indicators cannot fully reflect the health changes associated with abandoned mine exposure. The aim of this study was to identify biological changes in the residents of abandoned mine areas via proteomic analysis of their blood. Blood samples were collected from abandoned mine and control areas, and mass spectrometry was used for protein profiling. A total of 138 unique or common proteins that were differentially expressed in low-exposure abandoned mine area (LoAMA) or high-exposure abandoned mine area (HiAMA) compared to non-exposure control area (NEA) were analyzed, and identified 4 clusters based on functional similarity. Among the 10 proteins that showed specific change in LoAMA, 4 proteins(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) were cluded in cluster 1(plasma lipoprotein remodeling), and linked to proteins that showed specific change in protein expression in HiAMA. Therefore, it is suggested that 4 proteins are changed at low exposure to an abandoned mine (or initial exposure), and then at high exposure, changes in various proteins involved in linked plasma lipoprotein remodeling are induced, which might triggered by the 4 proteins. Interestingly, in addition to plasma lipoprotein remodeling, proteins involved in other functional networks were changed in the high exposure group. These were all directly or indirectly linked to the 4 biomarkers(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) that changed during low exposure. This suggests their potential utility in identifying areas impacted by abandoned mines. Especially, proteins involved in lipid metabolism and renal function-related diseases in individuals exposed to heavy metals in abandoned mine areas were correlated. Chronic kidney disease is predominantly instigated by cardiovascular disease and is commonly accompanied by dyslipidemia., Competing Interests: Declaration of competing interest Authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Stroke is an acute cerebrovascular disease in which blood flow to the brain is suddenly disrupted, causing damage to nerve cells. It involves complex and diverse pathophysiological processes and the treatment strategies are also diverse. The treatment for patients with stroke and atrial fibrillation (AF) is aimed at suppressing thrombus formation and migration. However, information regarding the protein networking involved in different thrombus formation pathways in patients with AF and stroke is insufficient. We performed protein profiling of patients with ischemic stroke with and without AF to investigate the mechanisms of thrombus formation and its pathophysiological association while providing helpful information for treating and managing patients with AF. These two groups were compared to identify the protein networks related to thrombus formation in AF. We observed that patients with ischemic stroke and AF had activated inflammatory responses induced by C-reactive protein, lipopolysaccharide-binding protein, and alpha-1-acid glycoprotein 1. In contrast, thyroid hormones were increased due to a decrease in transthyretin and retinol-binding protein 4 levels. The mechanism underlying enhanced cardiac activity, vasodilation, and the resulting thrombosis pathway were confirmed in AF. These findings will play an essential role in improving the prevention and treatment of AF-related stroke., (© 2024. The Author(s).)

Objective: Most prognostic indexes for ischemic stroke mortality lack radiologic information. We aimed to create and validate a deep learning-based mortality prediction model using brain diffusion weighted imaging (DWI), apparent diffusion coefficient (ADC), and clinical factors., Methods: Data from patients with ischemic stroke who admitted to tertiary hospital during acute periods from 2013 to 2019 were collected and split into training (n = 1109), validation (n = 437), and internal test (n = 654). Data from patients from secondary cardiovascular center was used for external test set (n = 507). The algorithm for predicting mortality, based on DWI and ADC (DLP_DWI), was initially trained. Subsequently, important clinical factors were integrated into this model to create the integrated model (DLP_INTG). The performance of DLP_DWI and DLP_INTG was evaluated by using time-dependent area under the receiver operating characteristic curves (TD AUCs) and Harrell concordance index (C-index) at one-year mortality., Results: The TD AUC of DLP_DWI was 0.643 in internal test set, and 0.785 in the external dataset. DLP_INTG had a higher performance at predicting one-year mortality than premise score in internal dataset (TD- AUC: 0.859 vs. 0.746; p = 0.046), and in external dataset (TD- AUC: 0.876 vs. 0.808; p = 0.007). DLP_DWI and DLP_INTG exhibited strong discrimination for the high-risk group for one-year mortality., Interpretation: A deep learning model using brain DWI, ADC and the clinical factors was capable of predicting mortality in patients with ischemic stroke., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

Cadmium (Cd), a serious environmental contaminant, is associated with adverse health effects. However, the specific changes that the human body experiences in response to exposure to varying concentrations of cadmium remain unknown. The high levels of heavy metal contamination, especially Cd, in abandoned mines and smelter sites make them ideal locations to investigate the physiological manifestations of Cd exposure. This study found that individuals inhabiting abandoned mine and smelter areas had higher concentrations of Cd in their urine and blood compared to those living outside these areas (i.e., the controls). Furthermore, proteomic profiling of blood samples from all study groups was performed to identify proteomic biomarkers associated with chronic and severe Cd exposure. This analysis showed statistically significant correlations between urine Cd levels and sixteen proteins. Among these proteins, seven exhibited significantly altered expressions in samples from contaminated areas compared with those from control areas. Therefore, these proteins were selected as potential markers representing Cd-related protein alterations. Multiple reaction monitoring analysis was performed to validate the expression patterns of the proteins and four proteins were found to exhibit consistent trends. The findings show that Cd exposure significantly affects the expression of certain proteins in the human body. Understanding the underlying mechanisms and diseases associated with Cd-induced protein alterations can aid in the development of effective preventive and therapeutic strategies for individuals exposed to Cd-linked pollution., Competing Interests: Declaration of competing interest Authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Major depressive disorder (MDD) has a high prevalence worldwide. Although the economic burden of depression increases annually, the proportion of patients with MDD receiving treatment did not increase between 2010 and 2018, suggesting an unmet treatment need. The burden of long-term treatment for depression is borne by patients. In this context, biomarkers associated with drug-treatment responses can be used as reference indicators to reduce unnecessary treatment and costs. Changes in biomolecules in response to drug treatment for depression and drug-treatment response markers have been studied extensively. The Hamilton Depression Rating Scale (HAM-D) is mainly used as an indicator of response and remission; however, it is difficult to determine whether the medication contributes to recovery when evaluating the effect of drug treatment for depression based on this assessment. Therefore, it is necessary to monitor the effect of medication compared to normal health conditions. Here, serum protein levels were compared using liquid chromatography-tandem mass spectrometry among a group of patients with depression who did not receive medication, a group of patients receiving medication, and a control group. Eight selected biomarkers, including Apolipoproteins A-I, Complement factor H, Complement C5, Complement C1q subcomponent subunit B, Alpha-2-HS-glycoprotein, Complement C1q subcomponent subunit C, Vitamin D-binding protein and Corticosteroid-binding globulin were distinguished between disease states, and protein levels in the drug-treated group were similar to those in the control group. These markers can be used to monitor the effectiveness of drug treatment., Competing Interests: Declaration of competing interest The authors declare that this study was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Purpose: Depressive mood is a major psychiatric symptom that causes serious disturbances in daily life. Unlike physical symptoms, psychiatric symptoms are more difficult to evaluate objectively. Therefore, we aimed to discover biomarkers that reflect changes in serum protein metabolism during a clinical depressive mood., Methods: Serum protein profiling was conducted in participants who were not experiencing a current depressive episode (healthy individuals and patients in remission). Serum proteins were identified and quantified using liquid chromatography-tandem mass spectrometry. Differentially expressed proteins with a p -value <0.05 were selected, and candidate biomarkers were verified using multiple reaction monitoring analysis for absolute quantification., Results: Apolipoprotein A-IV levels were lower in the group with a current episode of depression than in the remission and healthy control groups. Further, fibronectin levels were also lower in the group with a current episode of depression than in the healthy control group but not in the remission group., Conclusion: We found that apolipoprotein A-IV-mediated inflammation is involved in clinical depressive moods, possibly by inducing neurological changes in the brain. Therefore, apolipoprotein A-IV and fibronectin levels may be explored as potentially novel biomarkers for detecting a current episode of depression., Competing Interests: The authors declare no conflicts of interest in this work., (© 2023 Mun et al.)

Background and Aims: Diagnosis and classification of disease severity of major depressive disorder (MDD) are determined through a doctor's consultation and questionnaire-based rating scale. This study aimed to identify and validate a serum protein biomarker for diagnosing and classifying the disease severity of MDD., Materials and Methods: Based on the Hamilton Depression Rating Scale (HAMD) score, participants were divided into control, mild, moderate, and severe groups. Samples prepared from collected sera were analyzed using non-targeted qualitative and targeted quantitative tools to identify potential biomarkers., Results: Four proteins were selected as biomarker candidates, which showed statistically significant consistent tendencies depending on MDD severity. Among them, tetranectin was the only validated protein in the quantitative analysis that showed the same decreasing tendency as that in the qualitative analysis. Furthermore, tetranectin showed fair discrimination performance between the control and MDD group., Conclusions: Tetranectin may be a novel potential biomarker for diagnosing and classifying the severity of MDD, though further verification and validation studies of its efficacy are needed., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Bloodstain age estimation involves measuring time-dependent changes in the levels of biomolecules in bloodstains. Although several studies have identified bloodstain metabolites as markers for estimating bloodstain age, none have considered sex, age-related metabolomic differences, or long-time bloodstain age. Therefore, we aimed to identify metabolite markers for estimating the age of bloodstains at weekly intervals within 28 days and validate them through multiple reaction monitoring. Adenosine 5'-monophosphate, choline, and pyroglutamic acid were selected as markers. Seven metabolites were validated, including five previously reported metabolites, ergothioneine, hypoxanthine, L-isoleucine, L-tryptophan, and pyroglutamic acid. Choline and hypoxanthine can be used to differentiate bloodstains between days 0 and 14 after deposition at weekly intervals, whereas L-isoleucine and L-tryptophan can help distinguish bloodstains between 7 days before and 14 days after deposition. Evaluation of the changes in metabolite levels according to sex and age revealed that the average levels of all seven metabolites were higher in women on day 0. Moreover, the level of ergothioneine was significantly higher in elderly individuals than in young individuals at all time points. In this study, we confirmed the potential effectiveness of metabolites in bloodstains as forensic markers and provided a new perspective on metabolomic approaches linked to forensic science.

The study aims to determine the effect of virtual simulation practice in nursing students using the Virtual Patient Learning System Evaluation (VPLSE) tool. The study uses descriptive research, centering on correlation and regression analysis. 295 nursing students in Grades 3 and 4 who have experienced virtual simulation practice within the past year were included. The main variables of VPLSE comprise four sub-domains: nursing knowledge improvement, clinical competency development, confidence in nursing performance, and nursing care plan application. In addition to the VPLSE, two other tools, measuring virtual presence and self-efficacy, were utilized. The VPLSE was significantly positively correlated with virtual presence and self-efficacy, respectively. The VPLSE subdomain of "clinical competency development" had a strong positive correlation with virtual presence. To increase the effect of virtual simulation education, it is necessary to maintain the advantages of virtual simulation practice, such as freedom from space and time, repeated learning, psychological stability and application of nursing plans.

Classifying myocardial infarction by subtype is crucial for appropriate patient management. Although troponin is currently the most commonly used biomarker, it is not a specific marker for myocardial infarction and cannot distinguish subtypes. Furthermore, previous studies have confirmed that proteins known as myocardial infarction markers could function to distinguish the type of myocardial infarction. Therefore, we identify a marker that can distinguish type 1 myocardial infarction from other diseases with elevated troponin. We used mass spectrometry to compare type 1 myocardial infarction with other conditions characterized by troponin elevation and identified new candidate markers for disease classification. We then verified these markers, along with those already known to be associated with cardiovascular disease and plaque rupture. We identified α -1 acid glycoprotein 2, corticosteroid-binding globulin, and serotransferrin as potential distinguishing markers. The presence of these markers and other parameters, such as chest pain, electrocardiogram, and troponin levels from the complementary diagnostic processes, could provide valuable information to specifically diagnose type 1 myocardial infarction.

The volume of blood leaked from blood vessels may change due to evaporation of water under the natural influence of the external environment. Bloodstains and dried blood spots (DBS), which describes blood dried in the external environment, are similar in their production and their metabolite quantification profiles. In both bloodstain metabolite analysis in the forensic science field and DBS metabolite analysis in the clinical field, it is important to determine the volume of the origin blood as this affects metabolite quantification results. Therefore, the purpose of this study is to discover the internal standard metabolites that have quantitatively proportional relationships with origin blood volume and maintain constant concentrations even as the age of the bloodstain increases. As a result, the concentrations of L-isoleucine and L-phenylalanine increased in proportion to the origin blood volume of the bloodstain. The differences in concentration of L-isoleucine were significant in all volume comparisons except in the comparison between 65 μL and 85 μL. The differences in concentration of L-phenylalanine were significant in all volume comparisons except between 65 μL and 45 μL and between 65 μL and 85 μL. In addition, it was confirmed that both metabolites tended to maintain constant concentrations without being affected by bloodstain age as the volume became smaller. These internal standard metabolites can be used for estimating the origin blood volume of bloodstains during metabolite analysis of bloodstains and DBS and could provide a volume criterion for standardization when comparing metabolite quantification between samples., Competing Interests: Declaration of Interest The authors declare no conflicts of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Ergothioneine, which is a naturally occurring metabolite, generally accumulates in tissues and cells subjected to oxidative stress, owing to its structural stability at physiological pH; therefore, it has been attracting attention in various biomedical fields. Ergothioneine has also been suggested as a potential forensic marker, but its applicability has not yet been quantitatively validated. In this study, quantitative analysis of ergothioneine in bloodstains was conducted to estimate the age of bloodstains and that of bloodstain donors. Blood from youth and elderly participants was used to generate bloodstains. After extracting metabolites from the bloodstains under prevalent age conditions, ergothioneine levels were quantified by mass spectrometry via multiple reaction monitoring. The concentration of ergothioneine in day 0 bloodstains (fresh blood), was significantly higher in the elderly group than in the youth group, but it did not differ by sex. Statistically significant differences were observed between the samples from the two age groups on days 0, 5 and 7, and on days 2 and 3 compared with day 0. The findings suggest that ergothioneine can be used to estimate the age of bloodstains and of the donor; it could be useful as a potential marker in reconstructing crime scenes.

Major depressive disorder (MDD) is one of the most common psychiatric disorders that accompany psychophysiological and mood changes. However, the pathophysiology-based disease mechanism of MDD is not yet fully understood, and diagnosis is also conducted through interviews with clinicians and patients. Diagnosis and treatment of MDD are limited due to the absence of biomarkers underlying the pathophysiological mechanisms of MDD. Although various attempts have been made to discover metabolite biomarkers for the diagnosis and treatment response of MDD, problems with sample size and consistency of results have limited clinical application. In addition, it was reported that future biomarker studies must consider exposure to antidepressants, which is the main cause of heterogeneity in depression subgroups. Therefore, the purpose of this study is to discover and validate biomarkers for the diagnosis of depression in consideration of exposure to drug treatment including antidepressants that contribute to the heterogeneity of the MDD subgroup. In the biomarker discovery and validation set, the disease group consisted of a mixture of patients exposed and unexposed to drug treatment including antidepressants for the treatment of MDD. The serum metabolites that differed between the MDD patients and the control group were profiled using mass spectrometry. The validation set including the remission group was used to verify the effectiveness as a biomarker for the diagnosis of depression and determination of remission status. The presence of different metabolites between the two groups was confirmed through serum metabolite profiling between the MDD patient group and the control group. Finally, Acetylcarnitine was selected as a biomarker. In validation, acetylcarnitine was significantly decreased in MDD and was distinguished from remission status. This study confirmed that the discovered acetylcarnitine has potential as a biomarker for diagnosing depression and determining remission status, regardless of exposure to drug treatment including antidepressants., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lee, Mun, Lee, Choi, Joo, Kang and Lee.)

Metabolomic research using analytical chemistry methods has been carried out in a wide range of research fields. However, research combining forensic science and metabolomics is rare. Determining the age of bloodstains could provide key information regarding when a crime was committed. Currently, validated methods for estimating the age of bloodstains are unavailable. Metabolites are intermediate and final products of chemical reactions. Therefore, they are less likely to be degraded than other components of blood under field conditions. In this study, metabolites in bloodstains were analyzed using liquid chromatography-mass spectrometry to discover and validate metabolic markers for determining the age of bloodstains within a week post-bleeding. Nontargeted analysis of bloodstain metabolites revealed statistically significant differences over time. Quantitative analysis of identified candidates via multiple reaction monitoring confirmed the statistical significance according to the age of bloodstain. Pyroglutamic acid, l-glutamine, acetylcarnitine, and adenosine 5'-monophosphate were selected as the final markers. The content of each marker exhibited a statistically significant and consistent tendency to decrease with the age of bloodstain. Furthermore, the effect of hemolysis was considered according to the blood fraction spots of the four markers. This study is the first to identify and validate metabolite markers that may help determine the age of bloodstains within a week post-bleeding. If applied to crime scenes as indicators of the age of bloodstains, they can be used as innovative and important tools for reconstructing crime scenes, suggesting initial investigative direction. This study highlights the forensic utility of blood metabolites ex vivo.

Although radiation therapy (RT) plays an important role in the palliation of localized bone metastases, there is no consensus on a reliable method for evaluating treatment response. Therefore, we retrospectively evaluated the potential of magnetic resonance imaging (MRI) using apparent diffusion coefficient (ADC) maps and conventional images in whole-tumor volumetric analysis of texture features for assessing treatment response after RT. For this purpose, 28 patients who received RT for osteolytic bone metastasis and underwent both pre- and post-RT MRI were enrolled. Volumetric ADC histograms and conventional parameters were compared. Cox regression analyses were used to determine whether the change ratio in these parameters was associated with local disease progression-free survival (LDPFS). The ADC maximum, ADC mean, ADC median, ADC SD , maximum diameter, and volume of the target lesions after RT significantly increased. Change ratios of ADC mean < 1.41, tumor diameter ≥ 1.17, and tumor volume ≥ 1.55 were significant predictors of poor LDPFS. Whole-tumor volumetric ADC analysis might be utilized for monitoring patient response to RT and potentially useful in predicting clinical outcomes.

Background: Rheumatoid arthritis (RA) is an autoimmune disease of inflammatory joint damage, wherein C-reactive protein and autoantibodies including rheumatoid factor (RF) and anti-cyclic citrullinated peptide (anti-CCP) are rapidly elevated. These serological factors are diagnostic markers of RA; however, their sensitivity and specificity for prediction warrant improvement for an early and accurate diagnosis., Methods: We aimed to identify alternative biomarkers by serum protein profiling using LC-MS/MS. We performed statistical and functional analysis of differentially expressed proteins to identify biomarker candidates complementing conventional serological tests., Results: Seven biomarker candidates were verified through multiple reaction monitoring-based quantitative analysis, of which angiotensinogen (AGT), serum amyloid A-4 protein (SAA4), vitamin D-binding protein (VDBP), and retinol-binding protein-4 (RBP4) had an area under the curve over 0.8, thus distinguishing RA patients, including seronegative (RF- and anti-CCP-negative) RA patients, from healthy controls., Conclusions: Therefore, among seronegative RA patients, a four-biomarker panel (AGT, SAA4, VDBP, and RBP4) can prevent false negatives and help diagnose RA accurately.

Stroke has a high incidence rate and often leads to permanent disability, particularly if it is not treated promptly. However, no blood biomarkers for early diagnosis are available to date. Therefore, we sought to detect stroke-specific blood biomarkers by identifying proteins associated with the underlying coagulation mechanism, which accounts for more than 80% of all stroke cases. Protein profiling was performed using blood samples from 16 healthy controls and 18 patients who suffered a stroke as the discovery set. We identified upregulated proteins (> 1.5-fold change and p value < 0.05) in patients who suffered a stroke relative to the corresponding levels in healthy controls by nano-liquid chromatography-tandem mass spectrometry using data-independent acquisition based on sequential window acquisition of all theoretical mass spectra, which was developed to improve the consistency and accuracy of candidate proteins. Pathway analysis confirmed that the upregulated proteins were mainly involved in blood coagulation. Among these, we selected prothrombin, plasminogen, fibrinogen alpha-chain, and histidine-rich glycoprotein as candidate biomarkers. Multiple reaction monitoring analysis was performed on a validation set of 61 serum samples (31 healthy controls and 30 stroke patients) to assess the diagnostic value of the candidate biomarkers. All four proteins showed higher expression levels in patients with stroke than in healthy controls. The areas under the receiver operating characteristic curve were greater than 0.9, confirming their clinical value. These four blood coagulation proteins may help in diagnosing stroke more accurately and quickly.

Objective: To investigate the value of apparent diffusion coefficient (ADC) histogram analysis in predicting pelvic lymph node (LN) metastasis in patients with cervical cancer undergoing surgery., Materials and Methods: A total of 162 cervical cancer patients who underwent radical abdominal hysterectomy with pelvic LN dissection performed with pelvic 3 T-MRI including diffusion-weighted imaging were enrolled in this study. The ADC histogram variables (minimum, mean, median, 97.5th percentile [ADC 97.5 ], and maximum) of the tumors were developed using in-house software. For predicting pelvic LN metastasis, clinical and imaging variables were evaluated using logistic regression and receiver-operating characteristic (ROC) analyses., Results: Pelvic LN metastasis was identified histopathologically in 50 patients (30.9%). In patients with LN metastasis, all ADC histogram variables were significantly different from those without LN metastasis (all p < 0.01). Univariate analysis demonstrated that long- and short-axis diameter of LN, MRI T-stage, squamous cell carcinoma antigen, tumor size, and the ADC 97.5 were significantly associated with pelvic LN metastasis (all p < 0.05). However, multivariate analysis demonstrated that the ADC 97.5 was the only independent predictor of pelvic LN metastasis (odds ratio, 0.996; p = 0.001). The area under the ROC curve of ADC 97.5 was 0.782, which was the greatest among all variables. Interobserver agreement of all ADC histogram variables was fair to good., Discussion: The ADC 97.5 from histogram analysis may be a useful marker for the prediction of pelvic LN metastasis in patients with cervical cancer.

Objectives: To investigate the value of blood oxygenation level-dependent (BOLD) MRI as a predictor of clinical outcomes in cervical cancer patients treated with concurrent chemoradiotherapy (CCRT)., Method: Enrolled 92 patients with stage IB2-IVB cervical cancer who received CCRT underwent 3-T BOLD MRI before treatment. The R2* value (rate of spin dephasing, s -1 ) was measured in the tumor. Cox regression analysis was used to evaluate the associations of imaging and clinical parameters with progression-free survival (PFS) and cancer-specific survival (CSS). Inter-reader reliability for the R2* measurements was evaluated using an intraclass correlation coefficient (ICC)., Results: Tumor R2* values were significantly different between patients with and without disease progression (p < 0.001). Multivariate analysis demonstrated that tumor R2* value was significantly independent factor for PFS (hazard ratio [HR] = 5.746, p < 0.001) and CSS (HR = 12.878, p = 0.001). Additionally, squamous cell carcinoma antigen (HR = 1.027, p = 0.001) was significantly independent factor for PFS. Inter-reader reliability for the R2* measurements was good (ICC = 0.702)., Conclusion: Pretreatment 3-T BOLD MRI may be useful for predicting clinical outcomes in uterine cervical cancer patients treated with CCRT, with good inter-reader reliability., Key Points: • Tumor R2* values are different between patients with and without disease progression. • The R2* value is an independent factor for treatment outcomes in cervical cancer. • Inter-reader reliability for R2* measurements using BOLD MRI is good.

Purpose: Rheumatoid arthritis (RA) is an autoimmune disease in which autoantibodies attack the synovial membrane, causing joint inflammation. Blood tests would offer a powerful, minimally invasive method for early diagnosis of RA. However, no reliable biomarkers for RA are presently available. The aim is to develop biomarkers for RA by multiple reaction monitoring (MRM)-based quantification of candidate biomarkers., Experimental Design: Proteomics approaches are commonly used to identify and verify disease biomarkers. For discovery of biomarkers for RA, SWATH acquisition is performed and selected candidate biomarkers are validated by MRM. Target serum proteins are compared between patients with RA and healthy controls divided into three groups based on rheumatoid factor level., Results: A total of 45 differentially expressed proteins are identified, as determined by SWATH acquisition. Of these, 13 proteins are selected as novel candidate biomarkers. A total of five proteins (transthyretin, gelsolin, angiotensinogen, lipopolysaccharide-binding protein, and protein S100-A9) are shown to have the potential to distinguish patients with RA from healthy controls., Conclusions and Clinical Relevance: These five proteins may improve the efficiency of diagnosis of RA. MRM can be used to easily diagnose RA by detecting five proteins simultaneously in a single sample with high sensitivity., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Analysis of the components of bloodstains found at crime scenes can provide important information for solving the crime. However, components of blood and bloodstains vary with volume and various other unpredictable factors. Therefore, it is necessary to specify the volume of the initial liquid blood droplet and standardize the analysis. In this study, internal standard metabolites that remained constant in a certain amount of bloodstain, long after deposition of the stain, were identified. Liquid chromatography-electrospray ionization-tandem mass spectrometry of the metabolites extracted from the bloodstain samples at various time points (0, 7, 14, 21, and 28 days) was performed. The coefficient of variation (CV) of the obtained molecular features was calculated for each criterion: time point, subject, and all data (time and subject, triplicate of each). Five molecular features with average CVs of less than or equal to 5% were selected as candidates. Partial least squares discriminant analysis and principal component analysis showed that the effect on the candidates was very low over time. The fold-change value of abundances was confirmed according to time. Stigmasterol exhibited the most stable pattern; l-methionine remained stable until day 14 and after day 21. This study was the first attempt to identify internal standard metabolites that were maintained at a constant level in a bloodstain for a sufficiently long time. Analysis of internal standard metabolites in bloodstains will facilitate determination of the initial blood volume from which the bloodstain was made. Moreover, this method will provide an approach for standardization of bloodstains to obtain absolute quantitative information of bloodstain components at crime scenes., (Copyright © 2018. Published by Elsevier B.V.)

Objective: Hyperstimulation methods are broadly used for in vitro fertilization (IVF) in patients with infertility; however, the side effects associated with these therapies, such as ovarian hyperstimulation syndrome (OHSS), have not been well studied. N-glycoproteomes are subproteomes used for the remote sensing of ovarian stimulation in follicular growth. Glycoproteomic variation in human follicular fluid (hFF) has not been evaluated. In this study, we aimed to identify and quantify the glycoproteomes and N-glycoproteins (N-GPs) in natural and stimulated hFF using label-free nano-liquid chromatography/electrospray ionization-quad time-of-flight mass spectrometry., Methods: For profiling of the total proteome and glycoproteome, pooled protein samples from natural and stimulated hFF samples were selectively isolated using hydrazide chemistry to obtain the total proteomes and glycoproteomes. N-GPs were validated by the consensus sequence N-X-S/T (92.2% specificity for the N-glycomotif at p <0.05). All data were compared between natural versus hyperstimulated hFF samples., Results: We detected 41 and 44 N-GPs in the natural and stimulated hFF samples, respectively. Importantly, we identified 11 N-GPs with greater than two-fold upregulation in stimulated hFF samples compared to natural hFF samples. We also validated the novel N-GPs thyroxine-binding globulin, vitamin D-binding protein, and complement proteins C3 and C9., Conclusion: We identified and classified N-GPs in hFF to improve our understanding of follicular physiology in patients requiring assisted reproduction. Our results provided important insights into the prevention of hyperstimulation side effects, such as OHSS., Competing Interests: Conflict of interest: No potential conflict of interest relevant to this article was reported.

An azobenzene scaffold serves as both a fluorescence quencher and nitrogen mustard deactivator in a mitochondrial targeting unit bearing theranostic drug delivery system (DDS). The DDS exhibited a tissue selectivity for tumors with aggressive phenotypes, and the efficient in vitro and in vivo azoreduction under hypoxia conditions resulted in bright fluorescence at the tumor site as well as the in situ activation of the prodrug. In vivo therapeutic experiments demonstrated a significant reduction in tumor growth versus number of controls and ex vivo tissue analysis confirmed tissue normalization with strongly reduced angiogenic markers and suppressed cell proliferation. Mechanistic insight of the DDS's mode of action was gained by gene and protein expression experiments, aided by a proteomic analysis, revealing the circumvention of cellular drug resistance pathways as well as the normalization of Slit-Robo signaling, and the involvement of granzyme-triggered mitochondria-mediated apoptosis. Overall, the combined high sensitivity and synthetic ease as well as excellent therapeutic response suggests a revival of the azobenzene class of hypoxia activated drugs, especially applied to theranostics, is warranted., (Copyright © 2016 Elsevier Ltd. All rights reserved.)